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Erschienen in:
2024 | OriginalPaper | Buchkapitel
Prediction of Breast Cancer Using Convolution Neural Network
verfasst von : H. Aditya Pai, Piyush Kumar Pareek, A. Suresh Kumar, M. S. Guru Prasad
Erschienen in: Advances in Computing and Information
Verlag: Springer Nature Singapore
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Abstract
The Breast cancer is the a type of a carcinogenic cells that is developed in the breast and is more commonly found in women. This type of cancer has been found more fatal amongst women after the lung cancer. The paper proposes a study where it helps in identifying the breast cancer at faster rate using Convolution Neural Network (CNN). The paper uses a technique of identifies and differentiates the mammography pictures into three types, first one to be benign, second one is malignant, and the third one to be normal. This technique helps the medical professional in identifying the type of cancer. The CNN model used uses VGG-16 architecture for cancer detection and classification. The proposed system uses huge dataset of 275,000 RGB image patches. The proposed prediction is a deep learning technique where it’s architecture has two stages, first is image processing and the second is image classification. The result of using this technique reaches the accuracy level of 95.72% in classifying the different types of cancer.